Article

MB-SupCon: Microbiome-based predictive models via Supervised Contrastive Learning

2022-06-26

Abstract excerpt

Human microbiome consists of trillions of microorganisms. Microbiota can modulate the host physiology through molecule and metabolite interactions. Integrating microbiome and metabolomics data have the potential to predict different diseases more accurately. Yet, most datasets only measure microbiome data but without paired metabolome data. Here, we propose a novel integrative modeling framework, Microbiome-based...

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Literature Corpus work: 94aef16e-e666-5022-9849-1e7a9009a6b5
DOI: 10.1101/2022.06.23.497232

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